Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/poteto/noodle/schedulenpx skills add poteto/noodle --skill schedulegit clone --depth 1 https://github.com/poteto/noodleWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00067 | $0.01631 |
| Opus 5 | $0.00034 | $0.00816 |
| Sonnet 5 | $0.00013 | $0.00326 |
| Haiku 4.5 | $0.00007 | $0.00163 |
Grade A, and why
schedule scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Schedule
Read .noodle/mise.json, write .noodle/orders-next.json.
The loop atomically promotes orders-next.json into orders.json — never write orders.json directly.
Use noodle schema mise and noodle schema orders as the schema source of truth.
Operate fully autonomously. Never ask the user to choose or pause for confirmation.
One Plan at a Time
This is the cardinal scheduling rule. Pick the highest-priority plan with remaining phases and schedule all of them. Do not spread work across multiple plans — finishing one plan end-to-end produces shippable results; advancing many plans one phase each produces nothing usable. If the current plan is blocked, idle (empty orders) rather than context-switching to a different plan. Exception: shared infra orders can run alongside a plan's phases.
Orders Model
Output is {orders: [...]} where each order is a pipeline of stages executed sequentially. Group related work into stages within one order rather than separate orders.
Stages
Each stage has a do field (task key, must match a registered task type) and runs one at a time within the order. The loop advances to the next stage when the current one completes.
A typical order pipeline: execute, then quality, then reflect — all as stages of one order.
Task Types
Read task_types from mise to discover every schedulable task type and its schedule hint. Any registered task type can be a stage within an order. Use do on each stage to bind it to a task type.
Execute Tasks
Schedule execute tasks from the backlog array in mise. Use the backlog item ID (as a string) as the order id.
Backlog items always have id and title. Other fields are adapter-defined and may vary. The default adapter (todos.md) provides: status, section, tags, estimate, and plan. Custom adapters may include any fields — treat unknown fields as useful context.
Shared infrastructure: When multiple plans depend on common infrastructure (shared types, utilities, base packages), propose a standalone infra order before the plan's phases. Use a descriptive slug ID (e.g., "infra-shared-types"). If the infra work is substantial, create a backlog item via the adapter (noodle adapter run backlog add), then use that item's ID as the order ID.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 98 lines · 67 tokens per session scan A 61f91445cdf4
schedule is a skill published in the GitHub repository poteto/noodle (267 stars, last pushed 5mo ago), licensed MIT. It adds 67 tokens to every session and 1,631 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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